The Highly Cooperative Folding of Small Naturally Occurring Proteins Is Likely the Result of Natural Selection

Protein superfolds are characterised as frustration-free topologies: A case study of pure parallel β-sheet topologies

A protein superfold is a type of protein fold that is observed in at least three distinct, non-homologous protein families. Structural classification studies have revealed a limited number of prevalent superfolds alongside several infrequent occurring folds, and in α/β type superfolds, the C-terminal β-strand tends to favor the edge of the β-sheet, while the N-terminal β-strand is often found in the middle. The reasons behind these observations, whether they are due to evolutionary sampling bias or physical interactions, remain unclear. This article offers a physics-based explanation for these observations, specifically for pure parallel β-sheet topologies. Our investigation is grounded in several established structural rules that are based on physical interactions. We have identified "frustration-free topologies" which are topologies that can satisfy all the rules simultaneously. In contrast, topologies that cannot are termed "frustrated topologies." Our findings reveal that frustration-free topologies represent only a fraction of all theoretically possible patterns, these topologies strongly favor positioning the C-terminal β-strand at the edge of the β-sheet and the N-terminal β-strand in the middle, and there is significant overlap between frustration-free topologies and superfolds. We also used a lattice protein model to thoroughly investigate sequence-structure relationships. Our results show that frustration-free structures are highly designable, while frustrated structures are poorly designable. These findings suggest that superfolds are highly designable due to their lack of frustration, and the preference for positioning C-terminal β-strands at the edge of the β-sheet is a direct result of frustration-free topologies. These insights not only enhance our understanding of sequence-structure relationships but also have significant implications for de novo protein design.

The Effect of β-Sheet Secondary Structure on All-β Proteins by Molecular Dynamics Simulations

The effect of β-sheet ratio and chain length on all-β proteins was investigated by MD simulations. Protein samples composed of different repeating units with various β-sheet ratios or a different number of repeating units were simulated under a broad temperature range. The simulation results show that the smaller radius of gyration was achieved by the protein with the higher proportion of β-sheet secondary structure, which had the lower nonbonded energy with more HBs within the protein. The root mean square deviation (RMSD) and the root mean square fluctuation (RMSF) both increased with temperature, especially in the case of a longer chain. The visible period was also shown according to the repeated secondary structure. Several minimum values of RMSF were located on the skeleton of Cα atoms participating in the β-sheet, indicating that it is a kind of stable secondary structure. We also concluded that proteins with a short chain or a lower ratio of β-sheet could easily transform their oriented and compact structures to other ones, such as random coils, turns, and even α-helices. These results clarified the relationship from the primary level to the 3D structure of proteins and potentially predicted protein folding.

Protein dynamics: The future is bright and complicated!

Biological life depends on motion, and this manifests itself in proteins that display motion over a formidable range of time scales spanning from femtoseconds vibrations of atoms at enzymatic transition states, all the way to slow domain motions occurring on micro to milliseconds. An outstanding challenge in contemporary biophysics and structural biology is a quantitative understanding of the linkages among protein structure, dynamics, and function. These linkages are becoming increasingly explorable due to conceptual and methodological advances. In this Perspective article, we will point toward future directions of the field of protein dynamics with an emphasis on enzymes. Research questions in the field are becoming increasingly complex such as the mechanistic understanding of high-order interaction networks in allosteric signal propagation through a protein matrix, or the connection between local and collective motions. In analogy to the solution to the "protein folding problem," we argue that the way forward to understanding these and other important questions lies in the successful integration of experiment and computation, while utilizing the present rapid expansion of sequence and structure space. Looking forward, the future is bright, and we are in a period where we are on the doorstep to, at least in part, comprehend the importance of dynamics for biological function.

Coordinate-Dependent Drift-Diffusion Reveals the Kinetic Intermediate Traps of Top7-Based Proteins

The computer-designed Top7 served as a scaffold to produce immunoreactive proteins by grafting of the 2F5 HIV-1 antibody epitope (Top7-2F5) followed by biotinylation (Top7-2F5-biotin). The resulting nonimmunoglobulin affinity proteins were effective in inducing and detecting the HIV-1 antibody. However, the grafted Top7-2F5 design led to protein aggregation, as opposed to the soluble biotinylated Top7-2F5-biotin. The structure-based model predicted that the thermodynamic cooperativity of Top7 increases after grafting and biotin-labeling, reducing their intermediate state populations. In this work, the folding kinetic traps that might contribute to the aggregation propensity are investigated by the diffusion theory. Since the engineered proteins have similar sequence and structural homology, they served as protein models to study the kinetic intermediate traps that were uncovered by characterizing the position-dependent drift-velocity (v(Q)) and the diffusion (D(Q)) coefficients. These coordinate-dependent coefficients were taken into account to obtain the folding and transition path times over the free energy transition states containing the intermediate kinetic traps. This analysis may be useful to predict the aggregated kinetic traps of scaffold-epitope proteins that might compose novel diagnostic and therapeutic platforms.

Biotinylation Eliminates the Intermediate State of Top7 Designed with an HIV-1 Epitope

Broadly neutralizing antibodies against HIV-1 are rare with the 2F5 antibody being one of the most protective. Insertion of an antibody epitope into a stable and small protein scaffold overcomes many of the obstacles found to produce antibodies. However, the design leads to grafting of epitopes that may cause protein aggregation. Here, I investigated the 2F5 epitope grafted into the Top7 as the scaffold in which the resulting immunoreactive protein precipitates along the storage time, as opposed to its completely soluble biotinylated version. Molecular dynamics showed that biotinylation eliminates the intermediate state of the scaffold-epitope Top7-2F5 by switching a noncooperative to a cooperative folding. The aggregation propensity of the Top7-designed proteins is examined in light of thermodynamic cooperativity and kinetic traps along the decreasing depth of the intermediate ensemble in the free energy landscape. This protocol may predict stable and soluble scaffold-epitopes with the purpose of composing novel therapeutic and diagnostic platforms.

A Method for Assessing the Robustness of Protein Structures by Randomizing Packing Interactions

Many single-domain proteins are not only stable and water-soluble, but they also populate few to no intermediates during folding. This reduces interactions between partially folded proteins, misfolding, and aggregation, and makes the proteins tractable in biotechnological applications. Natural proteins fold thus, not necessarily only because their structures are well-suited for folding, but because their sequences optimize packing and fit their structures well. In contrast, folding experiments on the de novo designed Top7 suggest that it populates several intermediates. Additionally, in de novo protein design, where sequences are designed for natural and new non-natural structures, tens of sequences still need to be tested before success is achieved. Both these issues may be caused by the specific scaffolds used in design, i.e., some protein scaffolds may be more tolerant to packing perturbations and varied sequences. Here, we report a computational method for assessing the response of protein structures to packing perturbations. We then benchmark this method using designed proteins and find that it can identify scaffolds whose folding gets disrupted upon perturbing packing, leading to the population of intermediates. The method can also isolate regions of both natural and designed scaffolds that are sensitive to such perturbations and identify contacts which when present can rescue folding. Overall, this method can be used to identify protein scaffolds that are more amenable to whole protein design as well as to identify protein regions which are sensitive to perturbations and where further mutations should be avoided during protein engineering.

Tracking the ATP-binding response in adenylate kinase in real time

The biological function of proteins is critically dependent on dynamics inherent to the native structure. Such structural dynamics obey a predefined order and temporal timing to execute the specific reaction. Determination of the cooperativity of key structural rearrangements requires monitoring protein reactions in real time. In this work, we used time-resolved x-ray solution scattering (TR-XSS) to visualize structural changes in the Escherichia coli adenylate kinase (AdK) enzyme upon laser-induced activation of a protected ATP substrate. A 4.3-ms transient intermediate showed partial closing of both the ATP- and AMP-binding domains, which indicates a cooperative closing mechanism. The ATP-binding domain also showed local unfolding and breaking of an Arg¹³¹-Asp¹⁴⁶ salt bridge. Nuclear magnetic resonance spectroscopy data identified similar unfolding in an Arg¹³¹Ala AdK mutant, which refolded in a closed, substrate-binding conformation. The observed structural dynamics agree with a “cracking mechanism” proposed to underlie global structural transformation, such as allostery, in proteins.

Structural Characterization of the Cooperativity of Unfolding of a Heterodimeric Protein using Hydrogen Exchange-Mass Spectrometry

Little is known about how the sequence of structural changes in one chain of a heterodimeric protein is coupled to those in the other chain during protein folding and unfolding reactions, and whether individual secondary structural changes in the two chains occur in one or many coordinated steps. Here, the unfolding mechanism of a small heterodimeric protein, double chain monellin, has been characterized using hydrogen exchange-mass spectrometry. Transient structure opening, which enables HX, was found to be describable by a five state N ↔ I₁ ↔ I₂ ↔ I₃ ↔ U mechanism. Structural changes occur gradually in the first three steps, and cooperatively in the last step. β strands 2, 4 and 5, as well as the α-helix undergo transient unfolding during all three non-cooperative steps, while β1 and the two loops on both sides of the helix undergo transient unfolding during the first two steps. In the absence of GdnHCl, only β3 in chain A of the protein unfolds during the last cooperative step, while in the presence of 1 M GdnHCl, not only β3, but also β2 in chain B unfolds cooperatively. Hence, the extent of cooperative structural change and size of the cooperative unfolding unit increase when the protein is destabilized by denaturant. The naturally evolved two-chain variant of monellin folds and unfolds in a more cooperative manner than does a single chain variant created artificially, suggesting that increasing folding cooperativity, even at the cost of decreasing stability, may be a driving force in the evolution of proteins.

A hierarchy of coupling free energies underlie the thermodynamic and functional architecture of protein structures

Protein sequences and structures evolve by satisfying varied physical and biochemical constraints. This multi-level selection is enabled not just by the patterning of amino acids on the sequence, but also via coupling between residues in the native structure. Here, we employ an energetically detailed statistical mechanical model with millions of microstates to extract such long-range structural correlations, i.e. thermodynamic coupling free energies, from a diverse family of protein structures. We find that despite the intricate and anisotropic distribution of coupling patterns, the majority of residues (>70%) are only marginally coupled contributing to functional motions and catalysis. Physical origins of ‘sectors’, determinants of native ensemble heterogeneity in extant, ancient and designed proteins, and the basis for allostery emerge naturally from coupling free energies. The statistical framework highlights how evolutionary selection and optimization occur at the level of global interaction network for a given protein fold impacting folding, function, and allosteric outputs.

•

Evolution of protein structures occurs at the level of global interaction network.

•

More than 70% of the protein residues are weakly or marginally coupled.

•

Functional ‘sector’ regions are a manifestation of marginal coupling.

•

Coupling indices vary across the entire proteins in extant-ancient and natural-designed pairs.

•

The proposed methodology can be used to understand allostery and epistasis.

Computational and Experimental Assessment of Backbone Templates for Computational Redesign of the Thioredoxin Fold

Computational protein design has taken big strides in recent years; however, the tools available are still not at a state where a sequence can be designed to fold into a given protein structure at will and with high probability. We have applied here a recent release of Rosetta Design to redesign a set of structurally very similar proteins belonging to the thioredoxin fold. We used a genetic screening tool to estimate solubility/folding of the designed proteins in E. coli and to select the best hits from this for further biochemical characterization. We have previously used this set of template proteins for redesign and found that success was highly dependent on template structure, a trait which was also found in this study. Nevertheless, state-of-the-art design software is now able to predict the best template, most likely due to the introduction of an energy term that reports on stress in covalent bond lengths and angles. The template that led to the greatest fraction of successful designs was the same (a thioredoxin from spinach) as that identified in our previous study. Our previously described redesign of thioredoxin, which also used the spinach protein as a template, however also performed well as a template. In the present study, both of these templates yielded proteins with compact folded structures and enforced the conclusion that any design project must carefully consider different design templates. Fortunately, selecting designs based on energies appears to correctly identify such templates.

Revealing enzyme functional architecture via high-throughput microfluidic enzyme kinetics

Systematic and extensive investigation of enzymes is needed to understand their extraordinary efficiency and meet current challenges in medicine and engineering. We present HT-MEK (High-Throughput Microfluidic Enzyme Kinetics), a microfluidic platform for high-throughput expression, purification, and characterization of more than 1500 enzyme variants per experiment. For 1036 mutants of the alkaline phosphatase PafA (phosphate-irrepressible alkaline phosphatase of Flavobacterium), we performed more than 670,000 reactions and determined more than 5000 kinetic and physical constants for multiple substrates and inhibitors. We uncovered extensive kinetic partitioning to a misfolded state and isolated catalytic effects, revealing spatially contiguous regions of residues linked to particular aspects of function. Regions included active-site proximal residues but extended to the enzyme surface, providing a map of underlying architecture not possible to derive from existing approaches. HT-MEK has applications that range from understanding molecular mechanisms to medicine, engineering, and design.

The Stability Landscape of de novo TIM Barrels Explored by a Modular Design Approach

•

The TIM barrel is a versatile fold to understand structure-stability relationships.

•

A collection of de novo TIM barrels with improved hydrophobic cores was designed.

•

DeNovoTIMs are reversible in chemical and thermal unfolding, which is uncommon in TIM barrels.

•

Epistatic effects play a central role in DeNovoTIMs stabilization.

•

DeNovoTIMs navigate a previously uncharted region of the stability landscape.

The ability to design stable proteins with custom-made functions is a major goal in biochemistry with practical relevance for our environment and society. Understanding and manipulating protein stability provide crucial information on the molecular determinants that modulate structure and stability, and expand the applications of de novo proteins. Since the (β/⍺)₈-barrel or TIM-barrel fold is one of the most common functional scaffolds, in this work we designed a collection of stable de novo TIM barrels (DeNovoTIMs), using a computational fixed-backbone and modular approach based on improved hydrophobic packing of sTIM11, the first validated de novo TIM barrel, and subjected them to a thorough folding analysis. DeNovoTIMs navigate a region of the stability landscape previously uncharted by natural TIM barrels, with variations spanning 60 degrees in melting temperature and 22 kcal per mol in conformational stability throughout the designs. Significant non-additive or epistatic effects were observed when stabilizing mutations from different regions of the barrel were combined. The molecular basis of epistasis in DeNovoTIMs appears to be related to the extension of the hydrophobic cores. This study is an important step towards the fine-tuned modulation of protein stability by design.

Evolution, folding, and design of TIM barrels and related proteins

Proteins are chief actors in life that perform a myriad of exquisite functions. This diversity has been enabled through the evolution and diversification of protein folds. Analysis of sequences and structures strongly suggest that numerous protein pieces have been reused as building blocks and propagated to many modern folds. This information can be traced to understand how the protein world has diversified. In this review, we discuss the latest advances in the analysis of protein evolutionary units, and we use as a model system one of the most abundant and versatile topologies, the TIM-barrel fold, to highlight the existing common principles that interconnect protein evolution, structure, folding, function, and design.

Selection for cooperativity causes epistasis predominately between native contacts and enables epistasis-based structure reconstruction

Epistasis and cooperativity of folding both result from networks of energetic interactions in proteins. Epistasis results from energetic interactions among mutants, whereas cooperativity results from energetic interactions during folding that reduce the presence of intermediate states. The two concepts seem intuitively related, but it is unknown how they are related, particularly in terms of selection. To investigate their relationship, we simulated protein evolution under selection for cooperativity and separately under selection for epistasis. Strong selection for cooperativity created strong epistasis between contacts in the native structure but weakened epistasis between nonnative contacts. In contrast, selection for epistasis increased epistasis in both native and nonnative contacts and reduced cooperativity. Because epistasis can be used to predict protein structure only if it preferentially occurs in native contacts, this result indicates that selection for cooperativity may be key for predicting structure using epistasis. To evaluate this inference, we simulated the evolution of guanine nucleotide-binding protein (GB1) with and without cooperativity. With cooperativity, strong epistatic interactions clearly map out the native GB1 structure, while allowing the presence of intermediate states (low cooperativity) obscured the structure. This indicates that using epistasis measurements to reconstruct protein structure may be inappropriate for proteins with stable intermediates.

Protein sequence design by conformational landscape optimization

The protein design problem is to identify an amino acid sequence that folds to a desired structure. Given Anfinsen's thermodynamic hypothesis of folding, this can be recast as finding an amino acid sequence for which the desired structure is the lowest energy state. As this calculation involves not only all possible amino acid sequences but also, all possible structures, most current approaches focus instead on the more tractable problem of finding the lowest-energy amino acid sequence for the desired structure, often checking by protein structure prediction in a second step that the desired structure is indeed the lowest-energy conformation for the designed sequence, and typically discarding a large fraction of designed sequences for which this is not the case. Here, we show that by backpropagating gradients through the transform-restrained Rosetta (trRosetta) structure prediction network from the desired structure to the input amino acid sequence, we can directly optimize over all possible amino acid sequences and all possible structures in a single calculation. We find that trRosetta calculations, which consider the full conformational landscape, can be more effective than Rosetta single-point energy estimations in predicting folding and stability of de novo designed proteins. We compare sequence design by conformational landscape optimization with the standard energy-based sequence design methodology in Rosetta and show that the former can result in energy landscapes with fewer alternative energy minima. We show further that more funneled energy landscapes can be designed by combining the strengths of the two approaches: the low-resolution trRosetta model serves to disfavor alternative states, and the high-resolution Rosetta model serves to create a deep energy minimum at the design target structure.

Fuzziness and Frustration in the Energy Landscape of Protein Folding, Function, and Assembly

Are all protein interactions fully optimized? Do suboptimal interactions compromise specificity? What is the functional impact of frustration? Why does evolution not optimize some contacts? Proteins and their complexes are best described as ensembles of states populating an energy landscape. These ensembles vary in breadth from narrow ensembles clustered around a single average X-ray structure to broader ensembles encompassing a few different functional "taxonomic" states on to near continua of rapidly interconverting conformations, which are called "fuzzy" or even "intrinsically disordered". Here we aim to provide a comprehensive framework for confronting the structural and dynamical continuum of protein assemblies by combining the concepts of energetic frustration and interaction fuzziness. The diversity of the protein structural ensemble arises from the frustrated conflicts between the interactions that create the energy landscape. When frustration is minimal after folding, it results in a narrow ensemble, but residual frustrated interactions result in fuzzy ensembles, and this fuzziness allows a versatile repertoire of biological interactions. Here we discuss how fuzziness and frustration play off each other as proteins fold and assemble, viewing their significance from energetic, functional, and evolutionary perspectives.We demonstrate, in particular, that the common physical origin of both concepts is related to the ruggedness of the energy landscapes, intramolecular in the case of frustration and intermolecular in the case of fuzziness. Within this framework, we show that alternative sets of suboptimal contacts may encode specificity without achieving a single structural optimum. Thus, we demonstrate that structured complexes may not be optimized, and energetic frustration is realized via different sets of contacts leading to multiplicity of specific complexes. Furthermore, we propose that these suboptimal, frustrated, or fuzzy interactions are under evolutionary selection and expand the biological repertoire by providing a multiplicity of biological activities. In accord, we show that non-native interactions in folding or interaction landscapes can cooperate to generate diverse functional states, which are essential to facilitate adaptation to different cellular conditions. Thus, we propose that not fully optimized structures may actually be beneficial for biological activities of proteins via an alternative set of suboptimal interactions. The importance of such variability has not been recognized across different areas of biology.This account provides a modern view on folding, function, and assembly across the protein universe. The physical framework presented here is applicable to the structure and dynamics continuum of proteins and opens up new perspectives for drug design involving not fully structured, highly dynamic protein assemblies.

Complete and cooperative in vitro assembly of computationally designed self-assembling protein nanomaterials

Recent advances in computational methods have enabled the predictive design of self-assembling protein nanomaterials with atomic-level accuracy. These design strategies focus exclusively on a single target structure, without consideration of the mechanism or dynamics of assembly. However, understanding the assembly process, and in particular its robustness to perturbation, will be critical for translating this class of materials into useful technologies. Here we investigate the assembly of two computationally designed, 120-subunit icosahedral complexes in detail using several complementary biochemical methods. We found that assembly of each material from its two constituent protein building blocks was highly cooperative and yielded exclusively complete, 120-subunit complexes except in one non-stoichiometric regime for one of the materials. Our results suggest that in vitro assembly provides a robust and controllable route for the manufacture of designed protein nanomaterials and confirm that cooperative assembly can be an intrinsic, rather than evolved, feature of hierarchically structured protein complexes.

Recent advances in computational methods have enabled the predictive design of self-assembling protein nanomaterials with atomic-level accuracy. Here authors investigate the assembly of two computationally designed, 120-subunit icosahedral complexes and find that assembly of each material from its two constituent protein building blocks was highly cooperative.

Single molecule force spectroscopy reveals the context dependent folding pathway of the C-terminal fragment of Top7

Top7 is a de novo designed protein with atomic level accuracy and shows a folded structure not found in nature. Previous studies showed that the folding of Top7 is not cooperative and involves various folding intermediate states. In addition, various fragments of Top7 were found to fold on their own in isolation. These features displayed by Top7 are distinct from those of naturally occurring proteins of a similar size and suggest a rough folding energy landscape. However, it remains unknown if and how the intra-polypeptide chain interactions among the neighboring sequences of Top7 affect the folding of these Top7 fragments. Here we used single-molecule optical tweezers to investigate the folding–unfolding pathways of full length Top7 as well as its C-terminal fragment (CFr) in different sequence environments. Our results showed that the mechanical folding of Top7 involves an intermediate state that likely involves non-native interactions/structure. More importantly, we found that the folding of CFr is entirely dependent upon its sequence context in which it is located. When in isolation, CFr indeed folds into a cooperative structure showing near-equilibrium unfolding–folding transitions at ∼6.5 pN in OT experiments. However, CFr loses its autonomous cooperative folding ability and displays a folding pathway that is dependent on its interactions with its neighboring sequence/structure. This context-dependent folding dynamics and pathway of CFr are distinct from those of naturally occurring proteins and highlight the critical importance of intra-chain interactions in shaping the overall energy landscape and the folding pathway of Top7. These new insights may have important implications on the de novo design of proteins.

Optical tweezers experiments reveal that the folding of the C-terminal fragment of Top7 (cFr) is context-dependent. Depending on its neighboring sequence, cFr shows very different folding pathways and folding kinetics.

Computational prediction of protein aggregation: Advances in proteomics, conformation-specific algorithms and biotechnological applications

Protein aggregation is a widespread phenomenon that stems from the establishment of non-native intermolecular contacts resulting in protein precipitation. Despite its deleterious impact on fitness, protein aggregation is a generic property of polypeptide chains, indissociable from protein structure and function. Protein aggregation is behind the onset of neurodegenerative disorders and one of the serious obstacles in the production of protein-based therapeutics. The development of computational tools opened a new avenue to rationalize this phenomenon, enabling prediction of the aggregation propensity of individual proteins as well as proteome-wide analysis. These studies spotted aggregation as a major force driving protein evolution. Actual algorithms work on both protein sequences and structures, some of them accounting also for conformational fluctuations around the native state and the protein microenvironment. This toolbox allows to delineate conformation-specific routines to assist in the identification of aggregation-prone regions and to guide the optimization of more soluble and stable biotherapeutics. Here we review how the advent of predictive tools has change the way we think and address protein aggregation.

M. Brito R. Structure and Aggregation Mechanisms in Amyloids

The aggregation of a polypeptide chain into amyloid fibrils and their accumulation and deposition into insoluble plaques and intracellular inclusions is the hallmark of several misfolding diseases known as amyloidoses. Alzheimer′s, Parkinson′s and Huntington’s diseases are some of the approximately 50 amyloid diseases described to date. The identification and characterization of the molecular species critical for amyloid formation and disease development have been the focus of intense scrutiny. Methods such as X-ray and electron diffraction, solid-state nuclear magnetic resonance spectroscopy (ssNMR) and cryo-electron microscopy (cryo-EM) have been extensively used and they have contributed to shed a new light onto the structure of amyloid, revealing a multiplicity of polymorphic structures that generally fit the cross-β amyloid motif. The development of rational therapeutic approaches against these debilitating and increasingly frequent misfolding diseases requires a thorough understanding of the molecular mechanisms underlying the amyloid cascade. Here, we review the current knowledge on amyloid fibril formation for several proteins and peptides from a kinetic and thermodynamic point of view, the structure of the molecular species involved in the amyloidogenic process, and the origin of their cytotoxicity.

Water as a Good Solvent for Unfolded Proteins: Folding and Collapse are Fundamentally Different

The argument that the hydrophobic effect is the primary effect driving the folding of globular proteins is nearly universally accepted (including by the authors). But does this view also imply that water is a "poor" solvent for the unfolded states of these same proteins? Here we argue that the answer is "no," that is, folding to a well-packed, extensively hydrogen-bonded native structure differs fundamentally from the nonspecific chain collapse that defines a poor solvent. Thus, the observation that a protein folds in water does not necessitate that water is a poor solvent for its unfolded state. Indeed, chain-solvent interactions that are marginally more favorable than nonspecific intrachain interactions are beneficial to protein function because they destabilize deleterious misfolded conformations and inter-chain interactions.

Improving folding properties of computationally designed proteins

While the field of computational protein design has witnessed amazing progression in recent years, folding properties still constitute a significant barrier towards designing new and larger proteins. In order to assess and improve folding properties of designed proteins, we have developed a genetics-based folding assay and selection system based on the essential enzyme, orotate phosphoribosyl transferase from Escherichia coli. This system allows for both screening of candidate designs with good folding properties and genetic selection of improved designs. Thus, we identified single amino acid substitutions in two failed designs that rescued poorly folding and unstable proteins. Furthermore, when these substitutions were transferred into a well-structured design featuring a complex folding profile, the resulting protein exhibited native-like cooperative folding with significantly improved stability. In protein design, a single amino acid can make the difference between folding and misfolding, and this approach provides a useful new platform to identify and improve candidate designs.

The molecular basis of chaperone-mediated interleukin 23 assembly control

The functionality of most secreted proteins depends on their assembly into a defined quaternary structure. Despite this, it remains unclear how cells discriminate unassembled proteins en route to the native state from misfolded ones that need to be degraded. Here we show how chaperones can regulate and control assembly of heterodimeric proteins, using interleukin 23 (IL-23) as a model. We find that the IL-23 α-subunit remains partially unstructured until assembly with its β-subunit occurs and identify a major site of incomplete folding. Incomplete folding is recognized by different chaperones along the secretory pathway, realizing reliable assembly control by sequential checkpoints. Structural optimization of the chaperone recognition site allows it to bypass quality control checkpoints and provides a secretion-competent IL-23α subunit, which can still form functional heterodimeric IL-23. Thus, locally-restricted incomplete folding within single-domain proteins can be used to regulate and control their assembly.

It is unclear how unassembled secretory pathway proteins are discriminated from misfolded ones. Here the authors combine biophysical and cellular experiments to study the folding of heterodimeric interleukin 23 and describe how ER chaperones recognize unassembled proteins and aid their assembly into protein complexes while preventing the premature degradation of unassembled units.

Design of highly active double-pseudoknotted ribozymes: a combined computational and experimental study

Design of RNA sequences that adopt functional folds establishes principles of RNA folding and applications in biotechnology. Inverse folding for RNAs, which allows computational design of sequences that adopt specific structures, can be utilized for unveiling RNA functions and developing genetic tools in synthetic biology. Although many algorithms for inverse RNA folding have been developed, the pseudoknot, which plays a key role in folding of ribozymes and riboswitches, is not addressed in most algorithms. For the few algorithms that attempt to predict pseudoknot-containing ribozymes, self-cleavage activity has not been tested. Herein, we design double-pseudoknot HDV ribozymes using an inverse RNA folding algorithm and test their kinetic mechanisms experimentally. More than 90% of the positively designed ribozymes possess self-cleaving activity, whereas more than 70% of negative control ribozymes, which are predicted to fold to the necessary structure but with low fidelity, do not possess it. Kinetic and mutation analyses reveal that these RNAs cleave site-specifically and with the same mechanism as the WT ribozyme. Most ribozymes react just 50- to 80-fold slower than the WT ribozyme, and this rate can be improved to near WT by modification of a junction. Thus, fast-cleaving functional ribozymes with multiple pseudoknots can be designed computationally.

Selection and analyses of variants of a designed protein suggest importance of hydrophobicity of partially buried sidechains for protein stability at high temperatures

Computationally designed proteins of high stability provide specimen in addition to natural proteins for the study of sequence-structure stability relationships at the very high end of protein stability spectrum. The melting temperature of E_1r26, a protein we previously designed using the A Backbone-based Amino aCid Usage Survey (ABACUS) sequence design program, is above 110 °C, more than 50 °C higher than that of the natural thioredoxin protein whose backbone (PDB ID 1R26) has been used as the design target. Using an experimental selection approach, we obtained variants of E_1r26 that remain folded but are of reduced stability, including one whose unfolding temperature and denaturing guanidine concentration are similar to those of 1r26. The mutant unfolds with a certain degree of cooperativity. Its structure solved by X-ray crystallography agrees with that of 1r26 by a root mean square deviation of 1.3 Å, adding supports to the accuracy of the ABACUS method. Analyses of intermediate mutants indicate that the substitution of two partially buried hydrophobic residues (isoleucine and leucine) by polar residues (threonine and serine, respectively) are responsible for the dramatic change in the unfolding temperature. It is suggested that the effects of mutations located in rigid secondary structure regions, but not those in loops, may be well predicted through ABACUS mutation energy analysis. The results also suggest that hydrophobic effects involving intermediately buried sidechains can be critically important for protein stability at high temperatures.

Commonly used FRET fluorophores promote collapse of an otherwise disordered protein

The dimensions that unfolded proteins, including intrinsically disordered proteins (IDPs), adopt in the absence of denaturant remain controversial. We developed an analysis procedure for small-angle X-ray scattering (SAXS) profiles and used it to demonstrate that even relatively hydrophobic IDPs remain nearly as expanded in water as they are in high denaturant concentrations. In contrast, as demonstrated here, most fluorescence resonance energy transfer (FRET) measurements have indicated that relatively hydrophobic IDPs contract significantly in the absence of denaturant. We use two independent approaches to further explore this controversy. First, using SAXS we show that fluorophores employed in FRET can contribute to the observed discrepancy. Specifically, we find that addition of Alexa-488 to a normally expanded IDP causes contraction by an additional 15%, a value in reasonable accord with the contraction reported in FRET-based studies. Second, using our simulations and analysis procedure to accurately extract both the radius of gyration (R_g) and end-to-end distance (R_ee) from SAXS profiles, we tested the recent suggestion that FRET and SAXS results can be reconciled if the R_g and R_ee are "uncoupled" (i.e., no longer simply proportional), in contrast to the case for random walk homopolymers. We find, however, that even for unfolded proteins, these two measures of unfolded state dimensions remain proportional. Together, these results suggest that improved analysis procedures and a correction for significant, fluorophore-driven interactions are sufficient to reconcile prior SAXS and FRET studies, thus providing a unified picture of the nature of unfolded polypeptide chains in the absence of denaturant.

Networks of electrostatic and hydrophobic interactions modulate the complex folding free energy surface of a designed βα protein

The successful de novo design of proteins can provide insights into the physical chemical basis of stability, the role of evolution in constraining amino acid sequences, and the production of customizable platforms for engineering applications. Previous guanidine hydrochloride (GdnHCl; an ionic denaturant) experiments of a designed, naturally occurring βα fold, Di-III_14, revealed a cooperative, two-state unfolding transition and a modest stability. Continuous-flow mixing experiments in our laboratory revealed a simple two-state reaction in the microsecond to millisecond time range and consistent with the thermodynamic results. In striking contrast, the protein remains folded up to 9.25 M in urea, a neutral denaturant, and hydrogen exchange (HDX) NMR analysis in water revealed the presence of numerous high-energy states that interconvert on a time scale greater than seconds. The complex protection pattern for HDX corresponds closely with a pair of electrostatic networks on the surface and an extensive network of hydrophobic side chains in the interior of the protein. Mutational analysis showed that electrostatic and hydrophobic networks contribute to the resistance to urea denaturation for the WT protein; remarkably, single charge reversals on the protein surface restore the expected urea sensitivity. The roughness of the energy surface reflects the densely packed hydrophobic core; the removal of only two methyl groups eliminates the high-energy states and creates a smooth surface. The design of a very stable βα fold containing electrostatic and hydrophobic networks has created a complex energy surface rarely observed in natural proteins.

Pandoravirus Celtis Illustrates the Microevolution Processes at Work in the Giant Pandoraviridae Genomes

With genomes of up to 2.7 Mb propagated in μm-long oblong particles and initially predicted to encode more than 2000 proteins, members of the Pandoraviridae family display the most extreme features of the known viral world. The mere existence of such giant viruses raises fundamental questions about their origin and the processes governing their evolution. A previous analysis of six newly available isolates, independently confirmed by a study including three others, established that the Pandoraviridae pan-genome is open, meaning that each new strain exhibits protein-coding genes not previously identified in other family members. With an average increment of about 60 proteins, the gene repertoire shows no sign of reaching a limit and remains largely coding for proteins without recognizable homologs in other viruses or cells (ORFans). To explain these results, we proposed that most new protein-coding genes were created de novo, from pre-existing non-coding regions of the G+C rich pandoravirus genomes. The comparison of the gene content of a new isolate, pandoravirus celtis, closely related (96% identical genome) to the previously described p. quercus is now used to test this hypothesis by studying genomic changes in a microevolution range. Our results confirm that the differences between these two similar gene contents mostly consist of protein-coding genes without known homologs, with statistical signatures close to that of intergenic regions. These newborn proteins are under slight negative selection, perhaps to maintain stable folds and prevent protein aggregation pending the eventual emergence of fitness-increasing functions. Our study also unraveled several insertion events mediated by a transposase of the hAT family, 3 copies of which are found in p. celtis and are presumably active. Members of the Pandoraviridae are presently the first viruses known to encode this type of transposase.

Pressure-Temperature Analysis of the Stability of the CTL9 Domain Reveals Hidden Intermediates

The observation of two-state unfolding for many small single-domain proteins by denaturants has led to speculation that protein sequences may have evolved to limit the population of partially folded states that could be detrimental to fitness. How such strong cooperativity arises from a multitude of individual interactions is not well understood. Here, we investigate the stability and folding cooperativity of the C-terminal domain of the ribosomal protein L9 in the pressure-temperature plane using site-specific NMR. In contrast to apparent cooperative unfolding detected with denaturant-induced and thermal-induced unfolding experiments and stopped-flow refolding studies at ambient pressure, NMR-detected pressure unfolding revealed significant deviation from two-state behavior, with a core region that was selectively destabilized by increasing temperature. Comparison of pressure-dependent NMR signals from both the folded and unfolded states revealed the population of at least one invisible excited state at atmospheric pressure. The core destabilizing cavity-creating I98A mutation apparently increased the cooperativity of the loss of folded-state peak intensity while also increasing the population of this invisible excited state present at atmospheric pressure. These observations highlight how local stability is subtly modulated by sequence to tune protein conformational landscapes and illustrate the ability of pressure- and temperature-dependent studies to reveal otherwise hidden states.

The low populated folding intermediate of a mutant of the Fyn SH3 domain identified by a simple model

The low populated on-pathway folding intermediate of the A39V/N53P/V55L Fyn SH3 domain is captured by a native-centric model augmented by sequence-dependent nonnative hydrophobic interactions.

Protein Folding and Structure Prediction from the Ground Up II: AAWSEM for α/β Proteins

The atomistic associative memory, water mediated, structure and energy model (AAWSEM) is an efficient coarse-grained force field with transferable tertiary interactions that incorporates local in sequence energetic biases using structural information derived from all-atom simulations of long segments of the protein. For α helical proteins, the accuracy of structure prediction using AAWSEM has been established previously. In this article, we examine the capability of AAWSEM to predict the structure of α/β proteins. We also elaborate on an iterative approach that uses the structures from a first round of AAWSEM simulation as fragment memories. This iterative scheme improves the quality of the structure prediction and makes the free energy profile more funneled toward native configurations. We explore the use of clustering analyses as a way of evaluating the confidence in various structure prediction models. Clustering using a local relative order parameter (mutual Q) of the predicted structural ensemble turns out to be optimal. The tightest cluster according to mutual Q generally has the most correctly folded structure. Since there is no bioinformatic input, AAWSEM amounts to an ab initio protein structure prediction method that combines the efficiency of coarse-grained simulations with the local structural accuracy that can be achieved from all-atom simulations.

Computational Redesign of Thioredoxin Is Hypersensitive toward Minor Conformational Changes in the Backbone Template

Despite the development of powerful computational tools, the full-sequence design of proteins still remains a challenging task. To investigate the limits and capabilities of computational tools, we conducted a study of the ability of the program Rosetta to predict sequences that recreate the authentic fold of thioredoxin. Focusing on the influence of conformational details in the template structures, we based our study on 8 experimentally determined template structures and generated 120 designs from each. For experimental evaluation, we chose six sequences from each of the eight templates by objective criteria. The 48 selected sequences were evaluated based on their progressive ability to (1) produce soluble protein in Escherichia coli and (2) yield stable monomeric protein, and (3) on the ability of the stable, soluble proteins to adopt the target fold. Of the 48 designs, we were able to synthesize 32, 20 of which resulted in soluble protein. Of these, only two were sufficiently stable to be purified. An X-ray crystal structure was solved for one of the designs, revealing a close resemblance to the target structure. We found a significant difference among the eight template structures to realize the above three criteria despite their high structural similarity. Thus, in order to improve the success rate of computational full-sequence design methods, we recommend that multiple template structures are used. Furthermore, this study shows that special care should be taken when optimizing the geometry of a structure prior to computational design when using a method that is based on rigid conformations.

Protein Domain-Swapping Can Be a Consequence of Functional Residues

Monomer topology has been implicated in domain-swapping, a potential first step on the route to disease-causing protein aggregation. Despite having the same topology (β1-α1-β2-β3-β4-β5), the cysteine protease inhibitor stefin-B domain swaps more readily than a single-chain variant of the heterodimeric sweet protein monellin (scMn). Here, we computationally study the folding of stefin-B and scMn in order to understand the molecular basis for the difference in their domain-swapping propensities. In agreement with experiments, our structure-based simulations show that scMn folds cooperatively without the population of an intermediate while stefin-B populates an equilibrium intermediate state. Since the simulation intermediate has only one domain structured (β3-β4-β5), it can directly lead to domain-swapping. Using computational variants of stefin-B, we show that the population of this intermediate is caused by regions of stefin-B that have been implicated in protease inhibition. We also find that the protease-binding regions are located on two structural elements and localized in space. In contrast, the residues that contribute to the sweetness of monellin are not localized to a few structural elements but are distributed over the protein fold. We conclude that the distributed functional residues of monellin do not induce large local perturbations in the protein structure, eliminating the formation of folding intermediates and in turn domain-swapping. On the other hand, the localized protease-binding regions of stefin-B promote the formation of a folding intermediate which can lead to domain-swapping. Thus, domain-swapping can be a direct consequence of the constraints that function imposes on the protein structure.

Introduction of a polar core into the de novo designed protein Top7

Design of polar interactions is a current challenge for protein design. The de novo designed protein Top7, like almost all designed proteins, has an entirely nonpolar core. Here we describe the replacing of a sizable fraction (5 residues) of this core with a designed polar hydrogen bond network. The polar core design is expressed at high levels in E. coli, has a folding free energy of 10 kcal/mol, and retains the multiphasic folding kinetics of the original Top7. The NMR structure of the design shows that conformations of three of the five residues, and the designed hydrogen bonds between them, are very close to those in the design model. The remaining two residues, which are more solvent exposed, sample a wide range of conformations in the NMR ensemble. These results show that hydrogen bond networks can be designed in protein cores, but also highlight challenges that need to be overcome when there is competition with solvent.

Using natural sequences and modularity to design common and novel protein topologies

Protein design is still a challenging undertaking, often requiring multiple attempts or iterations for success. Typically, the source of failure is unclear, and scoring metrics appear similar between successful and failed cases. Nevertheless, the use of sequence statistics, modularity and symmetry from natural proteins, combined with computational design both at the coarse-grained and atomistic levels is propelling a new wave of design efforts to success. Here we highlight recent examples of design, showing how the wealth of natural protein sequence and topology data may be leveraged to reduce the search space and increase the likelihood of achieving desired outcomes.

The Folding of de Novo Designed Protein DS119 via Molecular Dynamics Simulations

As they are not subjected to natural selection process, de novo designed proteins usually fold in a manner different from natural proteins. Recently, a de novo designed mini-protein DS119, with a βαβ motif and 36 amino acids, has folded unusually slowly in experiments, and transient dimers have been detected in the folding process. Here, by means of all-atom replica exchange molecular dynamics (REMD) simulations, several comparably stable intermediate states were observed on the folding free-energy landscape of DS119. Conventional molecular dynamics (CMD) simulations showed that when two unfolded DS119 proteins bound together, most binding sites of dimeric aggregates were located at the N-terminal segment, especially residues 5-10, which were supposed to form β-sheet with its own C-terminal segment. Furthermore, a large percentage of individual proteins in the dimeric aggregates adopted conformations similar to those in the intermediate states observed in REMD simulations. These results indicate that, during the folding process, DS119 can easily become trapped in intermediate states. Then, with diffusion, a transient dimer would be formed and stabilized with the binding interface located at N-terminals. This means that it could not quickly fold to the native structure. The complicated folding manner of DS119 implies the important influence of natural selection on protein-folding kinetics, and more improvement should be achieved in rational protein design.

Designed protein reveals structural determinants of extreme kinetic stability

The design of stable, functional proteins is difficult. Improved design requires a deeper knowledge of the molecular basis for design outcomes and properties. We previously used a bioinformatics and energy function method to design a symmetric superfold protein composed of repeating structural elements with multivalent carbohydrate-binding function, called ThreeFoil. This and similar methods have produced a notably high yield of stable proteins. Using a battery of experimental and computational analyses we show that despite its small size and lack of disulfide bonds, ThreeFoil has remarkably high kinetic stability and its folding is specifically chaperoned by carbohydrate binding. It is also extremely stable against thermal and chemical denaturation and proteolytic degradation. We demonstrate that the kinetic stability can be predicted and modeled using absolute contact order (ACO) and long-range order (LRO), as well as coarse-grained simulations; the stability arises from a topology that includes many long-range contacts which create a large and highly cooperative energy barrier for unfolding and folding. Extensive data from proteomic screens and other experiments reveal that a high ACO/LRO is a general feature of proteins with strong resistances to denaturation and degradation. These results provide tractable approaches for predicting resistance and designing proteins with sufficient topological complexity and long-range interactions to accommodate destabilizing functional features as well as withstand chemical and proteolytic challenge.

Mapping the energy landscape for second-stage folding of a single membrane protein

Membrane proteins are designed to fold and function in a lipid membrane, yet folding experiments within a native membrane environment are challenging to design. Here we show that single-molecule forced unfolding experiments can be adapted to study helical membrane protein folding under native-like bicelle conditions. Applying force using magnetic tweezers, we find that a transmembrane helix protein, Escherichia coli rhomboid protease GlpG, unfolds in a highly cooperative manner, largely unraveling as one physical unit in response to mechanical tension above 25 pN. Considerable hysteresis is observed, with refolding occurring only at forces below 5 pN. Characterizing the energy landscape reveals only modest thermodynamic stability (ΔG = 6.5 kBT) but a large unfolding barrier (21.3 kBT) that can maintain the protein in a folded state for long periods of time (t1/2 ∼3.5 h). The observed energy landscape may have evolved to limit the existence of troublesome partially unfolded states and impart rigidity to the structure.

Topological and sequence information predict that foldons organize a partially overlapped and hierarchical structure

It has been suggested that proteins have substructures, called foldons, which can cooperatively fold into the native structure. However, several prior investigations define foldons in various ways, citing different foldon characteristics, thereby making the concept of a foldon ambiguous. In this study, we perform a Gō model simulation and analyze the characteristics of substructures that cooperatively fold into the native-like structure. Although some results do not agree well with the experimental evidence due to the simplicity of our coarse-grained model, our results strongly suggest that cooperatively folding units sometimes organize a partially overlapped and hierarchical structure. This view makes us easy to interpret some different proposal about the foldon as a difference of the hierarchical structure. On the basis of this finding, we present a new method to assign foldons and their hierarchy, using structural and sequence information. The results show that the foldons assigned by our method correspond to the intermediate structures identified by some experimental techniques. The new method makes it easy to predict whether a protein folds sequentially into the native structure or whether some foldons fold into the native structure in parallel.

Design of symmetric TIM barrel proteins from first principles

Background

Computational protein design is a rapidly maturing field within structural biology, with the goal of designing proteins with custom structures and functions. Such proteins could find widespread medical and industrial applications. Here, we have adapted algorithms from the Rosetta software suite to design much larger proteins, based on ideal geometric and topological criteria. Furthermore, we have developed techniques to incorporate symmetry into designed structures. For our first design attempt, we targeted the (α/β)₈ TIM barrel scaffold. We gained novel insights into TIM barrel folding mechanisms from studying natural TIM barrel structures, and from analyzing previous TIM barrel design attempts.

Methods

Computational protein design and analysis was performed using the Rosetta software suite and custom scripts. Genes encoding all designed proteins were synthesized and cloned on the pET20-b vector. Standard circular dichroism and gel chromatographic experiments were performed to determine protein biophysical characteristics. 1D NMR and 2D HSQC experiments were performed to determine protein structural characteristics.

Results

Extensive protein design simulations coupled with ab initio modeling yielded several all-atom models of ideal, 4-fold symmetric TIM barrels. Four such models were experimentally characterized. The best designed structure (Symmetrin-1) contained a polar, histidine-rich pore, forming an extensive hydrogen bonding network. Symmetrin-1 was easily expressed and readily soluble. It showed circular dichroism spectra characteristic of well-folded alpha/beta proteins. Temperature melting experiments revealed cooperative and reversible unfolding, with a T_m of 44 °C and a Gibbs free energy of unfolding (ΔG°) of 8.0 kJ/mol. Urea denaturing experiments confirmed these observations, revealing a C_m of 1.6 M and a ΔG° of 8.3 kJ/mol. Symmetrin-1 adopted a monomeric conformation, with an apparent molecular weight of 32.12 kDa, and displayed well resolved 1D-NMR spectra. However, the HSQC spectrum revealed somewhat molten characteristics.

Conclusions

Despite the detection of molten characteristics, the creation of a soluble, cooperatively folding protein represents an advancement over previous attempts at TIM barrel design. Strategies to further improve Symmetrin-1 are elaborated. Our techniques may be used to create other large, internally symmetric proteins.

Electronic supplementary material

The online version of this article (doi:10.1186/s12858-015-0047-4) contains supplementary material, which is available to authorized users.

Biophysics of protein evolution and evolutionary protein biophysics

The study of molecular evolution at the level of protein-coding genes often entails comparing large datasets of sequences to infer their evolutionary relationships. Despite the importance of a protein's structure and conformational dynamics to its function and thus its fitness, common phylogenetic methods embody minimal biophysical knowledge of proteins. To underscore the biophysical constraints on natural selection, we survey effects of protein mutations, highlighting the physical basis for marginal stability of natural globular proteins and how requirement for kinetic stability and avoidance of misfolding and misinteractions might have affected protein evolution. The biophysical underpinnings of these effects have been addressed by models with an explicit coarse-grained spatial representation of the polypeptide chain. Sequence-structure mappings based on such models are powerful conceptual tools that rationalize mutational robustness, evolvability, epistasis, promiscuous function performed by 'hidden' conformational states, resolution of adaptive conflicts and conformational switches in the evolution from one protein fold to another. Recently, protein biophysics has been applied to derive more accurate evolutionary accounts of sequence data. Methods have also been developed to exploit sequence-based evolutionary information to predict biophysical behaviours of proteins. The success of these approaches demonstrates a deep synergy between the fields of protein biophysics and protein evolution.

Predicting aggregation-prone sequences in proteins

Owing to its association with a diverse range of human diseases, the determinants of protein aggregation are studied intensively. It is generally accepted that the effective aggregation tendency of a protein depends on many factors such as folding efficiency towards the native state, thermodynamic stability of that conformation, intrinsic aggregation propensity of the polypeptide sequence and its ability to be recognized by the protein quality control system. The intrinsic aggregation propensity of a polypeptide sequence is related to the presence of short APRs (aggregation-prone regions) that self-associate to form intermolecular β-structured assemblies. These are typically short sequence segments (5-15 amino acids) that display high hydrophobicity, low net charge and a high tendency to form β-structures. As the presence of such APRs is a prerequisite for aggregation, a plethora of methods have been developed to identify APRs in amino acid sequences. In the present chapter, the methodological basis of these approaches is discussed, as well as some practical applications.

Protein stability versus function: effects of destabilizing missense mutations on BRCA1 DNA repair activity

The majority of the unstable BRCA1 BRCT domain missense mutations we studied disrupted DNA repair in vivo, but reduced cellular function only weakly correlated with reduced structural stability. The findings have an impact on assessing cancer susceptibility in patients with BRCA1 mutations.

A compact native 24-residue supersecondary structure derived from the villin headpiece subdomain

Many small proteins fold highly cooperatively in an all-or-none fashion and thus their native states are well protected from thermal fluctuations by an extensive network of interactions across the folded structure. Because protein structures are stabilized by local and nonlocal interactions among distal residues, dissecting individual substructures from the context of folded proteins results in large destabilization and loss of unique three-dimensional structure. Thus, mini-protein substructures can only rarely be derived from natural templates. Here, we describe a compact native 24-residues-long supersecondary structure derived from the hyperstable villin headpiece subdomain consisting of helices 2 and 3 (HP24). Using a combination of experimental techniques, including NMR and small-angle x-ray scattering, as well as all-atom replica exchange molecular-dynamics simulations, we show that a variant with stabilizing substitutions (HP24stab) forms a densely packed and compact conformation. In HP24stab, interactions between helices 2 and 3 are similar to those observed in native folded HP35, and the two helices cooperatively stabilize each other by completing the hydrophobic core lining the central part of HP35. Interestingly, even though the HP24wt fragment shows a more expanded and less structured conformation, NMR and simulations demonstrate a preference for a native-like topology. Thus, the two stabilizing residues in HP24stab shift the energy balance toward the native state, leading to a minimal folding motif.